• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1216-1221
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• 2005

The GPS software receiver based on the SDR(Software Defined Radio) technology provides the ability to easily adopt other signal processing algorithms without changing or modifying the hardware of the GPS receiver. However, it is difficult to implement the GPS software receiver using a commercial processor because of heavy computation load for processing the GPS signals in real time. This paper proposes an efficient GPS signal processing scheme and correlator structure to reduce the computation load for processing the GPS signal in the GPS software receiver, which uses a patterned look-up table method to generate the correlation value between the GPS signals and the replica signals. In this paper, it is explained that the computation load of the proposed scheme is much smaller than that of the previous GPS signal processing scheme. Finally, the processing time of the proposed scheme is compared with that of the previous scheme, and the improvement is shown from the viewpoint of the computation load.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1329-1336
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• 1996

In many image compression applications, the discrete cosine transform (DCY) is well known for is highly efficient coding performance. However, it produces undesirable block artifacts in low-bit rate coding. In addition, in many practical applications, faster computation and easier VLST implementation of DCT coefficients are also important issues. The removal of the block artifacts and faster DCT computation are therefor of practical interest. In this paper, a modified DCTcomputation scheme was investigated, which provides a simple efficient solution to the reduction of the block artifacts while achieving faster computation. We have applied the new ap-proach to the low-bit rate coding and decoding of images. Simulation results on real images have verified the improved performance of the proposed method over the standar d method.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.271-286
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• 2011

In this paper, we propose efficient algorithms for parallel prefix computation and sorting on a recursive dual-net. The recursive dual-net $RDN^k$(B) for k > 0 has $(2n_o)^{2K}/2$ nodes and $d_0$ + k links per node, where $n_0$ and $d_0$ are the number of nod es and the node-degree of the base-network B, respectively. Assume that each node holds one data item, the communication and computation time complexities of the algorithm for parallel prefix computation on $RDN^k$(B), k > 0, are $2^{k+1}-2+2^kT_{comm}(0)$ and $2^{k+1}-2+2^kT_{comp}(0)$, respectively, where $T_{comm}(0)$ and $T_{comp}(0)$ are the communication and computation time complexities of the algorithm for parallel prefix computation on the base-network B, respectively. The algorithm for parallel sorting on $RDN^k$(B) is restricted on B = $Q_m$ where $Q_m$ is an m-cube. Assume that each node holds a single data item, the sorting algorithm runs in $O((m2^k)^2)$ computation steps and $O((km2^k)^2)$ communication steps, respectively.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1221-1224
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• 2003

A 64-point R2$^2$ SDF pipeline FFT processor using a new efficient computation sharing multiplier was designed. Computation sharing multiplication specifically targets computation re-use in multiplication of coefficient vector by scalar and is effectively used in DSP(Digital Signal Processing). To reduce the number of multipliers in FFT, we used the proposed computation sharing multiplier. The 64-point pipeline FFT processor was implemented by VHDL and synthesized using Max+PLUSII of Altera. The simulation result shows that the proposed computation sharing multiplier can be reduced to about 17.8% logic cells compared with a conventional multiplier. This processor can operate at 33MHz and calculate a 64-point pipeline FFT in 1.94 $mutextrm{s}$.

• Journal of Information Technology Services
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• v.3 no.2
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• pp.99-104
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• 2004

Conventional and public-key cryptography has been widely accepted as a base technology for the design of computer security systems. D-classes have the potential for application to conventional and public-key cryptography. However, there are very few results on D-classes because the computational complexity of D-class computation is NP-complete. This paper discusses the design of algorithms for the efficient computation of D-classes and the Java implementation of them. In addition, the paper implements the same D-class computation algorithms in C and shows the performance of C and Java programming languages for the computation-intensive applications by comparing their execution results.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.597-604
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• 2007

Stream data is a continuous flow of information that mostly arrives as the form of an infinite rapid stream. Recently researchers show a great deal of interests in analyzing such data to obtain value added information. Here, we propose an efficient cube computation algorithm for multidimensional analysis of stream data. The fact that stream data arrives in an unsorted fashion and aggregation results can only be obtained after the last data item has been read. cube computation requires a tremendous amount of memory. In order to resolve such difficulties, we compute user selected aggregation fables only, and use a combination of an way and AVL trees as a temporary storage for aggregation tables. The proposed cube computation algorithm works even when main memory is not large enough to store all the aggregation tables during the computation. We showed that the proposed algorithm is practically fast enough by theoretical analysis and performance evaluation.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.455-464
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• 2012

Due to the recent data explosion, methods which can meet the requirement of large data analysis has been studying. This paper proposes MRIterativeBUC algorithm which enables efficient computation of large data cube by distributed parallel processing with MapReduce framework. MRIterativeBUC algorithm is developed for efficient iterative operation of the BUC method with MapReduce, and overcomes the limitations about the storage size and processing ability caused by large data cube computation. It employs the idea from the iceberg cube which computes only the interesting aspect of analysts and the distributed parallel process of cube computation by partitioning and sorting. Thus, it reduces data emission so that it can reduce network overload, processing amount on each node, and eventually the cube computation cost. The bottom-up cube computation and iterative algorithm using MapReduce, proposed in this paper, can be expanded in various way, and will make full use of many applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.477-487
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• 2017

Multiparty computation (MPC) is a computation technique where many participants provide their data and jointly compute operations to get a computation result. Earlier MPC protocols were mostly depended on communication between the users. Several schemes have been presented that mainly work by delegating operations to two non-colluding servers. Peter et al. propose a protocol that perfectly eliminates the need of users' participation during the whole computation process. However, the drawback of their scheme is the excessive dependence on the server communication. To cater this issue, we propose a protocol that reduce server communication overhead using the proxy re-encryption (PRE). Recently, some authors have put forward their efforts based on the PRE. However, these schemes do not achieve the desired goals and suffer from attacks that are based on the collusion between users and server. This paper, first presents a comprehensive analysis of the existing schemes and then proposes a secure and efficient MPC protocol. The proposed protocol completely eliminates the need of users' participation, incurs less communication overhead and does not need to solve the discrete logarithm problem (DLP) in order to get the computation results.

• Journal of Korean Society of Rural Planning
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• v.5 no.1 s.9
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• pp.20-25
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• 1999

Our interest in this paper is in the efficient computation of a good low bound for the traveling salesman problem and is in the application of a network problem in agriculture. We base our approach on a relatively new formulation of the TSP as a two-commodity network flow problem. By assigning Lagrangian multipliers to certain constraints and relaxing them, the problem separates into two single-commodity network flow problems and an assignment problem, for which efficient algorithms are available.